"participants who had access to an AI assistant wrote significantly less secure code" and "were also more likely to believe they wrote secure code" - 2023 Stanford University study published at CCS23

It seems to me that if one can adequately explain the function of their pseudocode in adequate detail for an LLM to turn it into a functional and reliable program, then the hardest part of writing the code was already done without the LLM.

Not specified for this research but... if you rely on LLM to write code that is security-sensitive, I don't expect you to write secured code without LLM anyway

I'm doing my part by writing really shitty foss projects for AI to steal and train on.

No worries, the properly implemented CI/CD pipelines will catch the bad code!

I had a student came into office hours asking why their program got a bad grade. I looked and it didn't actually do anything related to the assignment.

Upon further query, they objected saying that the CI pipeline built it just fine.

So ..yeah... You can write a program that builds and runs, but doesn't do the required tasks, which makes it wrong. This was not a concept they'd figured out yet.
- Shouldn't the pipeline have failed unless the functional tests passed?
Until you find out those were also built by a junior using an llm to help 🙃

I really don't get how its different than a search engine. Granted its surprising how often I have to give up in disgust and just go back to normal search but pretty often they can find more relevant stuff faster

I really don’t get how its different than a search engine

Neither did this guy.

The difference is that LLM output is (in the formal sense) bullshit.
- so is search. I mean I would not click the first link from a search and then copy and paste code from the site into my project no questions asked. similarly you can look over what the ai comes up with and see if it makes sense. same you would do with some dudes blog. you can also check the references it gives or ask it to expand on some part. hey what does the function X do. I really don't see it as being worse than search.
People like to gatekeep easy access to knowledge for some reason.

2023? Like last year? Like when LLMs were just a curiosity more than anything useful?

They should be doing these studies continuously...

Edit: Oh no, I forgot Lemmy hates LLMs. Oh well, can't blame you guys, hate is the basic manifestation towards what scares you, and it's revealing.

Unlike this year when LLMs are more of a huge scam.
- We're entering the 'blockchain for every need' stage. Expect massive money to flow into scams, poor ideas, and outright dangerous uses for a few years .
  
  Before Blockchain we had 'the web' itself in the dot com era. Before that? I saw it in basic computing as a solution to everything.
- Curious why your perspective is they're are more of a scam when by all metrics they've only improved in accuracy?
I'm sure they will, here's year one.
They do. Reality is not going to change though. You can enable a handicapped developer to code with LLMs, but you can't win a foot race by using a wheelchair.
- I'm just waiting for someone to lecture me how the speed record in wheelchair sprint beats feet's ass...
Hmm. To me 2023 was the breakthrough year for them. Now we are already getting used to their flaws.
Hmmm, it's almost like the study was testing peoples perception of the usefulness of AI vs the actual usefulness and results that came out.
While I agree “they should be doing these studies continuously” point of view, I think the bigger red flag here is that with the advancements of AI, a study published in 2023 (meaning the experiment was done much earlier) is deeply irrelevant today in late 2024. It feels misleading and disingenuous to be sharing this today.
- No. I would suggest you actually read the study.
  
  The problem that the study reveals is that people who use AI-generated code as a rule don't understand it and aren't capable of debugging it. As a result, bigger LLMs will not change that.
- Its the inherent disconnect between "News" and "Science".
  
  Science requires rigorous study and incremental advancement. A 2023 article based on 2022 data is inherently understood to be.. 2022 data (note: I did not actually check but that is the timeline I assume. It is in the study).
  
  But news and social media just want headlines that get people angry and reinforce whatever nonsense people want to Believe.
  
  It is similar to explaining basic concepts. Been a minute since the last time I was properly briefed, but think stuff like "Do NOT say 'theory' of evolution. Instead, talk about how evolution is the only accepted justification based on evidence and research"